Acute effects of an arginine-based supplement on neuromuscular, ventilatory, and metabolic fatigue thresholds during cycle ergometry
Bibliographic record
Abstract
The purpose of the present study was to examine the effects of an acute dose of an arginine-based supplement on the physical working capacity at the fatigue threshold (PWCFT), lactate threshold (LT), ventilatory threshold (VT), and peak oxygen uptake during incremental cycle ergometry. This study used a double-blinded, placebo-controlled, within-subjects crossover design. Nineteen untrained men (mean age ± SD = 22.0 ± 1.7 years) were randomly assigned to ingest either the supplement (3.0 g of arginine, 300 mg of grape seed extract, and 300 mg of polyethylene glycol) or placebo (microcrystalline cellulose) and performed an incremental test on a cycle ergometer for determination of PWCFT, LT, VT, and peak oxygen uptake. Following a 1-week period, the subjects returned to the laboratory and ingested the opposite substance (either supplement or placebo) prior to completing another incremental test to be reassessed for PWCFT, LT, VT, and peak oxygen uptake. The paired-samples t tests indicated there were significant (P < 0.05) mean differences between the arginine and placebo conditions for the PWCFT (192 ± 42 vs. 168 ± 53 W, respectively) and VT (2546 ± 313 vs. 2452 ± 342 mL·min(-1)), but not the LT (135 ± 26 vs. 138 ± 22 W), absolute peak oxygen uptake (3663 ± 445 vs. 3645 ± 438 mL·min(-1)), or relative peak oxygen uptake (46.5 ± 6.0 vs. 46.2 ± 5.0 mL·kg(-1)·min(-1)). These findings suggested that the arginine-based supplement may be used on an acute basis for delaying the onset of neuromuscular fatigue (i.e., PWCFT) and improving the VT in untrained individuals.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".